vichayturen commented on code in PR #64:
URL:
https://github.com/apache/incubator-hugegraph-ai/pull/64#discussion_r1719170313
##########
hugegraph-llm/src/hugegraph_llm/demo/rag_web_demo.py:
##########
@@ -433,6 +486,78 @@ def apply_embedding_configuration(arg1, arg2, arg3):
out = gr.Textbox(label="Output", show_copy_button=True)
btn = gr.Button("(BETA) Init HugeGraph test data (🚧WIP)")
btn.click(fn=init_hg_test_data, inputs=inp, outputs=out) # pylint:
disable=no-member
+ return hugegraph_llm
+
+
+def rag_web_http_api():
+ @app.post("/rag")
+ def graph_rag_api(req: RAGRequest):
+ result = graph_rag(req.query, req.raw_llm, req.vector_only,
req.graph_only, req.graph_vector)
+ return {key: value for key, value in zip(
+ ["raw_llm", "vector_only", "graph_only", "graph_vector"], result)
if getattr(req, key)}
+
+ @app.post("/graph/config")
+ def graph_config_api(req: GraphConfigRequest):
+ # Accept status code
+ status_code = apply_graph_configuration(req.ip, req.port, req.name,
req.user, req.pwd, req.gs)
+
+ if status_code == -1:
+ return {"message":"Unsupported HTTP method"}
+
+ if 200 <= status_code < 300:
+ return {"message":"Connection successful. Configured finished."}
+ else:
+ return {"message":f"Connection failed with status code:
{status_code}"}
+
+ @app.post("/llm/config")
+ def llm_config_api(req: LLMConfigRequest):
+ settings.llm_type = req.llm_type
+
+ if req.llm_type == "openai":
+ status_code = apply_llm_configuration(req.api_key, req.api_base,
req.language_model, req.max_tokens)
+ elif req.llm_type == "qianfan_wenxin":
+ status_code = apply_llm_configuration(req.api_key, req.secret_key,
req.language_model, None)
+ else:
+ status_code = apply_llm_configuration(req.host, req.port,
req.language_model, None)
+
+ if status_code == -1:
+ return {"message":"Unsupported HTTP method"}
+
+ if 200 <= status_code < 300:
+ return {"message":"Connection successful. Configured finished."}
+ else:
+ return {"message":f"Connection failed with status code:
{status_code}"}
+
+ @app.post("/embedding/config")
+ def embedding_config_api(req: LLMConfigRequest):
+ settings.embedding_type = req.llm_type
+
+ if req.llm_type == "openai":
+ status_code = apply_embedding_configuration(req.api_key,
req.api_base, req.language_model)
+ elif req.llm_type == "qianfan_wenxin":
+ status_code = apply_embedding_configuration(req.api_key,
req.api_base, None)
Review Comment:
At present, this function does not return a value
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